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A Rao-Blackwellized Mixed State Particle Filter for Head Pose Tracking

Publications associées (39)

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A Rao-Blackwellized Mixed State Particle Filter for Head Pose Tracking

Jean-Marc Odobez, Silèye Oumar Ba

This paper presents a Rao-Blackwellized mixed state particle filter for joint head tracking and pose estimation. Rao-Blackwellizing a particle filter consists of marginalizing some of the variables of the state space in order to exactly compute their poste ...

2005

Proposal strategies for joint state-space tracking with particle filters

Volkan Cevher

A proposal function determines the random particle support of a particle filter. When this support is distributed close to the true target density, filter's estimation performance increases for a given number of particles. In this paper, a proposal strateg ...

2005

An acoustic multiple target tracker

Volkan Cevher

We propose a particle filter acoustic tracker to track multiple maneuvering targets using a state space formulation with a locally linear motion model. The observations are a batch of direction-of-arrival (DOA) estimates at various frequencies. The data li ...

2005

General direction-of-arrival tracking with acoustic nodes

Volkan Cevher

In this paper, we propose a particle filter acoustic direction-of-arrival (DOA) tracker to track multiple maneuvering targets using a state space approach. The particle filter determines its state vector using a batch of DOA estimates. The filter likelihoo ...

Institute of Electrical and Electronics Engineers2005

A Probabilistic Interpretation of SVMs with an Application to Unbalanced Classification

Samy Bengio

In this paper, we show that the hinge loss can be interpreted as the neg-log-likelihood of a semi-parametric model of posterior probabilities. From this point of view, SVMs represent the parametric component of a semi-parametric model fitted by a maximum a ...

IDIAP2005

A Probabilistic Interpretation of SVMs with an Application to Unbalanced Classification

Samy Bengio

2005

Tracking People in Meetings with Particles

Daniel Gatica-Perez, Jean-Marc Odobez, Guillaume Lathoud, Silèye Oumar Ba, Kevin Smith

Automatic meeting analysis is an emerging research field. In this paper, we present stochastic algorithms for tracking people in multi-sensor meeting rooms, for a number of relevant tasks, including tracking multiple people, tracking head pose towards anal ...

2005

General state-space models

Thomas Gsponer

In time series analysis state-space models provide a wide and flexible class. The basic idea is to describe an unobservable phenomenon of interest on the basis of noisy data. The first constituent of such a model is the so-called state equation, which char ...

EPFL2004

Tracking People in Meetings with Particles

Daniel Gatica-Perez, Jean-Marc Odobez, Guillaume Lathoud, Silèye Oumar Ba, Kevin Smith

IDIAP2004

A probabilistic framework for joint head tracking and pose estimation

Jean-Marc Odobez, Silèye Oumar Ba

Head Tracking and pose estimation are usually considered as two sequential and separate problems: pose is estimated on the head patch provided by a tracking module. However, precision in head pose estimation is dependent on tracking accuracy which itself c ...

2004